Use of Some Exponential Smoothing Models in Forecasting Some Food Crop Prices in the Upper East Region of Ghana

The study was designed to compare the performance of Holt-Winters multiplicative method with Double exponential smoothing method in forecasting future prices of some selected food crops in the Upper East Region of Ghana and also to examine the trend or direction of movement of the prices. The conclusion drawn from the study was that the prices have been rising since January 1992, decreasing sometimes but not below the January 1992 prices. This is an indication that all things being equal, the prices of the selected food crops will keep rising (rising trend). Results from the study revealed that the double exponential smoothing performed better, in four of the five selected food crops in which trend was present, than the Holt-Winters multiplicative method. That is the double exponential model forecasted prices which were much closer to the observed values than the Holt-Winters model. However in the case of the prices of groundnut in which both seasonality and trend were present the Holt-Winters model performed better than the double exponential smoothing. This is a confirmation of the norm that the Holt-Winters model performs better when both trend and seasonality are present whilst the double exponential smoothing performs better when trend is present in a set of data (Minitab User’s Guide 2,). Results from the study also showed that the double exponential smoothing model performs better when given the optimal values. However the optimal values given by the study lie outside the suggested range (0.70 and 0.95) for exponential smoothing methods. The study revealed that in practice the discount factors could lie outside the suggested range for exponential smoothing. From the study it will be recommended that double exponential smoothing models be used for modelling and forecasting the prices of cereals crops  in which trend is present whilst the Holt-Winters multiplicative method is used for the leguminous crops in which both trend and seasonality are present in the Upper East Region of Ghana

The Contribution of Women to Household Food Security in the Kassena -Nankana East District in the Upper East Region of Ghana

The study examines the contribution of women in food production and its impact on food security in the Kassena Nankana district of the upper east region of Ghana.  The specific objectives are: to examine the socio-economic characteristics of women farmers in the area, the challenges they face in food production The study utilizes both primary and secondary data. Primary data were obtained through questionnaire administration and direct observation in the study area. 160 questionnaires were administered purposively to 160 women who are into food production and live stock production while the secondary sources were obtained from review of related literature on the subject matter. Data collected were analysed through descriptive statistics. Results revealed that majority of the women are into food production in the area than their male counterparts, it also revealed that women are discriminated when it comes to decision making with regards to land acquisitions and credit facilities. The study also revealed that about 97% of the women in the study are into food crop farming which they use to feed their housed hold. Key Words: women, food security, household

Assessing the Performance of ELL and EBP Models in Estimating District Level Poverty Indices in The Presence of Outliers in the Northern Region of Ghana.

The objective of this study was to assess the performance of the Elbers, Lanjouw and Lanjouw (ELL) and the Empirical Best Predictor (EBP) Small Area Estimation (SAE) models in estimating the Foster-Greer-Thobecke (FGT) poverty indices for the Northern Region of Ghana in the presence of outliers. The sixth round of the Ghana Living Standard Survey (GLSS) data and the Population and Housing Census ( PHC) data were used for the study. The performances of these SAE models under normality and non-normality assumptions were evaluated by computing and comparing their Absolute Relative Biases and Relative Root Mean Squared Errors values under both conditions by conducting a model-based simulation study in the absence and presence of outlier contaminated data. Results from the study showed that no matter the level of contamination, the EBP model is a better performer and more stable than the ELL model in estimating all the FGT poverty indicators for the Region. Therefore, it was recommended that in future poverty estimating exercises, the EBP model be used to estimate the FGT poverty indicators for the Northern Region of Ghana